Projects
Projects: Projects for Investigator |
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| Reference Number | EP/M507167/1 | |
| Title | Intelligent SME Energy Management and Trading with Ancillary Services | |
| Status | Completed | |
| Energy Categories | Energy Efficiency(Residential and commercial) 50%; Other Power and Storage Technologies(Electricity transmission and distribution) 15%; Other Cross-Cutting Technologies or Research(Environmental, social and economic impacts) 35%; |
|
| Research Types | Basic and strategic applied research 100% | |
| Science and Technology Fields | SOCIAL SCIENCES (Economics and Econometrics) 25%; PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 25%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 25%; ENGINEERING AND TECHNOLOGY (Architecture and the Built Environment) 25%; |
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| UKERC Cross Cutting Characterisation | Systems Analysis related to energy R&D (Energy modelling) 50%; Sociological economical and environmental impact of energy (Other sociological economical and environmental impact of energy) 50%; |
|
| Principal Investigator |
Dr AC Rogers No email address given Electronics and Computer Science University of Southampton |
|
| Award Type | Standard | |
| Funding Source | EPSRC | |
| Start Date | 01 November 2014 | |
| End Date | 30 September 2015 | |
| Duration | 11 months | |
| Total Grant Value | £203,902 | |
| Industrial Sectors | Energy; Information Technologies | |
| Region | South East | |
| Programme | Energy : Energy | |
| Investigators | Principal Investigator | Dr AC Rogers , Electronics and Computer Science, University of Southampton (100.000%) |
| Web Site | ||
| Objectives | ||
| Abstract | The core vision of this project is the development and pilot of a low cost, robust platform for intelligent building energyusage that, combined with a new peer-to-peer energy market system, will facilitate localised energy trading and enableparticipation of small to medium enterprises in National Grid balancing services.The academic researchers, will work with commercial lead KiwiPower to:(i) Develop algorithms that learn the thermal performance of the commercial building in which the building managementsystem is installed, enabling optimal control of the building's heating and air conditioning system during demand responseperiods (where, for example, air conditioning use will be optimally curtailed to reduce peak loads without adversely affectingthe comfort of the building's occupants).(ii) Design, develop and evaluate and effective local energy market in which autonomous trading agents representing bothindividual buildings and also standalone generation and storage facilities can interact to optimally balance energy demandagainst local generation and storage capacity.The new platform and market will enable SMEs to control and monitor their production and consumption assets, toautomatically manage supply and demand at a localised level, and respond to national balancing requirements andfinancial incentives to shift demand.This project is innovative as:(i) The novel low cost intelligent energy system, incorporating learning algorithms, overcomes existing cost barriers forSMEs, enabling them to benefit from the latest energy optimisation algorithms to reduce costs and improve efficiency.(ii) It will prove the technical and commercial viability of localised peer-to-peer energy markets and the ability for SMEs to be involved in national electricity balancing services | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 11/12/14 | |
